Artificial Intelligence and Health Equity: A Conceptual Framework for Inclusive Innovation

Abstract

Artificial intelligence (AI) is reshaping healthcare by enhancing diagnostic accuracy, optimizing workflows, and enabling precision medicine. However, without intentional safeguards, AI risks exacerbating health disparities through the use of biased data, opaque algorithms, and unequal access. This conceptual paper develops a comprehensive framework for inclusive AI innovation, synthesizing insights from sociology, public health, and AI ethics. The framework comprises five interrelated components: data representativeness, fairness and transparency mechanisms, participatory design, governance and accountability, and continuous monitoring. Together, these elements embed equity at every stage of AI development and deployment, ensuring that technological advancement aligns with justice and beneficence. The paper argues that participatory approaches and regulatory oversight are essential for building trust and operationalizing fairness. This model provides policymakers, developers, and healthcare organizations with a roadmap for translating ethical principles into practice, fostering a healthcare ecosystem that is both technologically advanced and socially inclusive.